Metabolic Subtypes Predict Treatment Response in Acute Myeloid Leukemia: A Pilot Study.

Area of Science:

• Metabolomics and Multi-omics Integration
• Cancer Biology
• Precision Medicine

Background:

• Acute myeloid leukemia (AML) treatment response varies significantly.
• Understanding dynamic metabolic changes in AML is crucial for predicting outcomes.
• Current subtyping methods do not fully capture longitudinal metabolic shifts.

Purpose of the Study:

• To develop a dynamic metabolic subtyping system for AML.
• To integrate longitudinal metabolomics and multi-omics data.
• To evaluate the system's ability to predict treatment response in AML patients.

Main Methods:

• Enrolled 29 AML patients for untargeted serum metabolomics (pre- and post-treatment).
• Classified patients into metabolic subtypes (G1/G2 pre-treatment, TG1/TG2 post-treatment) based on pathway combinations.
• Integrated baseline transcriptome data and validated in external cohorts; utilized single-cell and spatial transcriptomics.

Main Results:

• Pre-treatment subtype G2 showed a significantly higher complete remission (CR) rate (71%) than G1 (29%).
• Post-treatment subtype TG2 had an 83% CR rate versus 17% in TG1.
• Co-localization of CA2-high immature erythrocytes and neutrophils observed in non-CR patients, linking G1 phenotype to resistance.

Conclusions:

• Dynamic metabolic subtyping (G1/G2, TG1/TG2) strongly correlates with AML treatment response.
• Identified cellular niches (erythrocytes, neutrophils) associated with chemotherapy resistance in AML.
• Findings support combining dynamic metabolic subtyping with microenvironmental features for precision AML therapy.